For baseline comparisons, we consider the two main configurations of the max-ent algorithm presented in [1]}. In particular, we use statistical rate setting \( \rho = 1 \)  and prior interpolation parameter \( C = 0.5 \)  with a marginal vector constraint determined by: (1) the weighted mean from [1]} \( \theta ^{w} \) ; and (2) the empirical expectation vector with the marginal set to ensure equal representation of the sensitive attribute \( \theta ^{b} \) .
We denote the two distributions as \( \texttt {M.Ent} \)  \( \theta ^{c} \)  and \( \texttt {M.Ent} \)  \( \theta ^{b} \) .
We do not use this baseline in the synthetic dataset as there is no prediction task, i.e., there is no statistical rate.
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